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  <section id="concatenate">
<h1>concatenate<a class="headerlink" href="#concatenate" title="Permalink to this headline">¶</a></h1>
<section id="documentation">
<h2>Documentation<a class="headerlink" href="#documentation" title="Permalink to this headline">¶</a></h2>
<dl class="py function">
<dt id="treetensor.numpy.concatenate">
<code class="sig-prename descclassname">treetensor.numpy.</code><code class="sig-name descname">concatenate</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">arrays</span></em>, <em class="sig-param"><span class="o">*</span><span class="n">args</span></em>, <em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="../../_modules/treetensor/numpy/funcs.html#concatenate"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#treetensor.numpy.concatenate" title="Permalink to this definition">¶</a></dt>
<dd></dd></dl>

<div class="tip admonition">
<p class="admonition-title">Numpy Version Related</p>
<p>This documentation is based on
<a class="reference external" href="https://numpy.org/doc/1.21/reference/generated/numpy.concatenate.html">numpy.concatenate</a>
in <a class="reference external" href="https://numpy.org/doc/1.21/">numpy v1.21.6</a>.
<strong>Its arguments’ arrangements depend on the version of numpy you installed</strong>.</p>
<p>If some arguments listed here are not working properly, please check your numpy’s version
with the following command and find its documentation.</p>
<div class="highlight-shell notranslate"><div class="highlight"><table class="highlighttable"><tr><td class="linenos"><div class="linenodiv"><pre><span class="normal">1</span></pre></div></td><td class="code"><div><pre><span></span>python -c <span class="s1">&#39;import numpy as np;print(np.__version__)&#39;</span>
</pre></div></td></tr></table></div>
</div>
<p>The arguments and keyword arguments supported in numpy v1.21.6 is listed below.</p>
</div>
</section>
<section id="description-from-numpy-v1-21">
<h2>Description From Numpy v1.21<a class="headerlink" href="#description-from-numpy-v1-21" title="Permalink to this headline">¶</a></h2>
<dl class="py function">
<dt id="numpy.concatenate">
<code class="sig-prename descclassname">numpy.</code><code class="sig-name descname">concatenate</code><span class="sig-paren">(</span><em class="sig-param">(a1</em>, <em class="sig-param">a2</em>, <em class="sig-param">...)</em>, <em class="sig-param">axis=0</em>, <em class="sig-param">out=None</em>, <em class="sig-param">dtype=None</em>, <em class="sig-param">casting=&quot;same_kind&quot;</em><span class="sig-paren">)</span><a class="headerlink" href="#numpy.concatenate" title="Permalink to this definition">¶</a></dt>
<dd><p>Join a sequence of arrays along an existing axis.</p>
</dd></dl>

<section id="parameters">
<h3>Parameters<a class="headerlink" href="#parameters" title="Permalink to this headline">¶</a></h3>
<blockquote>
<div><dl>
<dt>a1, a2, … : sequence of array_like</dt><dd><p>The arrays must have the same shape, except in the dimension
corresponding to <cite>axis</cite> (the first, by default).</p>
</dd>
<dt>axis : int, optional</dt><dd><p>The axis along which the arrays will be joined.  If axis is None,
arrays are flattened before use.  Default is 0.</p>
</dd>
<dt>out : ndarray, optional</dt><dd><p>If provided, the destination to place the result. The shape must be
correct, matching that of what concatenate would have returned if no
out argument were specified.</p>
</dd>
<dt>dtype : str or dtype</dt><dd><p>If provided, the destination array will have this dtype. Cannot be
provided together with <cite>out</cite>.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 1.20.0.</span></p>
</div>
</dd>
<dt>casting : {‘no’, ‘equiv’, ‘safe’, ‘same_kind’, ‘unsafe’}, optional</dt><dd><p>Controls what kind of data casting may occur. Defaults to ‘same_kind’.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 1.20.0.</span></p>
</div>
</dd>
</dl>
</div></blockquote>
</section>
<section id="returns">
<h3>Returns<a class="headerlink" href="#returns" title="Permalink to this headline">¶</a></h3>
<blockquote>
<div><dl class="simple">
<dt>res : ndarray</dt><dd><p>The concatenated array.</p>
</dd>
</dl>
</div></blockquote>
</section>
<section id="see-also">
<h3>See Also<a class="headerlink" href="#see-also" title="Permalink to this headline">¶</a></h3>
<blockquote>
<div><p>ma.concatenate : Concatenate function that preserves input masks.
array_split : Split an array into multiple sub-arrays of equal or</p>
<blockquote>
<div><p>near-equal size.</p>
</div></blockquote>
<p>split : Split array into a list of multiple sub-arrays of equal size.
hsplit : Split array into multiple sub-arrays horizontally (column wise).
vsplit : Split array into multiple sub-arrays vertically (row wise).
dsplit : Split array into multiple sub-arrays along the 3rd axis (depth).
stack : Stack a sequence of arrays along a new axis.
block : Assemble arrays from blocks.
hstack : Stack arrays in sequence horizontally (column wise).
vstack : Stack arrays in sequence vertically (row wise).
dstack : Stack arrays in sequence depth wise (along third dimension).
column_stack : Stack 1-D arrays as columns into a 2-D array.</p>
</div></blockquote>
</section>
<section id="notes">
<h3>Notes<a class="headerlink" href="#notes" title="Permalink to this headline">¶</a></h3>
<blockquote>
<div><p>When one or more of the arrays to be concatenated is a MaskedArray,
this function will return a MaskedArray object instead of an ndarray,
but the input masks are <em>not</em> preserved. In cases where a MaskedArray
is expected as input, use the ma.concatenate function from the masked
array module instead.</p>
</div></blockquote>
</section>
<section id="examples">
<h3>Examples<a class="headerlink" href="#examples" title="Permalink to this headline">¶</a></h3>
<blockquote>
<div><div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">a</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">],</span> <span class="p">[</span><span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">]])</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">b</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">]])</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">((</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">),</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="go">array([[1, 2],</span>
<span class="go">       [3, 4],</span>
<span class="go">       [5, 6]])</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">((</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="o">.</span><span class="n">T</span><span class="p">),</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="go">array([[1, 2, 5],</span>
<span class="go">       [3, 4, 6]])</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">((</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">),</span> <span class="n">axis</span><span class="o">=</span><span class="kc">None</span><span class="p">)</span>
<span class="go">array([1, 2, 3, 4, 5, 6])</span>
</pre></div>
</div>
<p>This function will not preserve masking of MaskedArray inputs.</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">a</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ma</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">3</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">a</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ma</span><span class="o">.</span><span class="n">masked</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">b</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="mi">5</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">a</span>
<span class="go">masked_array(data=[0, --, 2],</span>
<span class="go">             mask=[False,  True, False],</span>
<span class="go">       fill_value=999999)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">b</span>
<span class="go">array([2, 3, 4])</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">concatenate</span><span class="p">([</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">])</span>
<span class="go">masked_array(data=[0, 1, 2, 2, 3, 4],</span>
<span class="go">             mask=False,</span>
<span class="go">       fill_value=999999)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">np</span><span class="o">.</span><span class="n">ma</span><span class="o">.</span><span class="n">concatenate</span><span class="p">([</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">])</span>
<span class="go">masked_array(data=[0, --, 2, 2, 3, 4],</span>
<span class="go">             mask=[False,  True, False, False, False, False],</span>
<span class="go">       fill_value=999999)</span>
</pre></div>
</div>
</div></blockquote>
</section>
</section>
</section>


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